Predicting Consumers’ Usage Intention Towards User-Generated Content: A Hybrid SEM-ANN Approach

Smriti Mathur (), Alok Tewari (), Avinash K. Shrivastava, Vimal Chandra Verma (), Sushant Kumar Vishnoi () and Preeti Sharma ()
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Smriti Mathur: School of Business and Management, Christ University, Delhi NCR Campus, Ghaziabad, U.P., India
Alok Tewari: School of Management, Babu Banarasi Das University, Lucknow, U.P., India
Avinash K. Shrivastava: International Management Institute Kolkata, Kolkata, West Bengal, India
Vimal Chandra Verma: BBA Department, Siddharth University, Siddharth Nagar, U.P., India
Sushant Kumar Vishnoi: Department of Marketing, Institute of Management Studies, Ghaziabad, U.P., India
Preeti Sharma: School of Business Studies, Sharda University, Greater Noida, U.P., India

Journal of Information & Knowledge Management (JIKM), 2025, vol. 24, issue 01, 1-31

Abstract: With the change in the communication pattern, end-users are engaging in creating content and referring to the content created by other users while making purchase decisions. This research aims at modelling factors affecting consumers’ usage intention (UI) towards user-generated content (UGC) using Need for Cognition (NfC) as a moderator of the proposed relationships. The factors affecting consumers’ UI involve perceived usefulness (PU), source credibility (SC), information quality (IQ) and NfC. Further, a novel attempt has been made by using the neural network approach to assess the predictive accuracy of the model. A structured questionnaire was used to collect data from 298 consumers through a survey. Data were analysed using two-stage structural equation modelling (SEM) and artificial neural network (ANN). All the independent variables viz., PU, SC, IQ and NfC significantly affect attitude towards UGC, which in turn affects UI. Results of multi-group analysis and a series of chi-square difference tests reveal that a NfC significantly moderates the relationship between PU and attitude, as well as that between SC and attitude. The root mean square error values from the neural network analysis suggest that the models show good predictive accuracy. This study provides a novel assessment of the usage of a hybrid SEM-ANN approach for understanding of UGC by incorporating NfC as a moderator in shaping consumers’ attitudes and intentions to use UGC.

Keywords: User-generated content; perceived usefulness; source credibility; information quality; need for cognition; attitude; usage intention; moderation; neural network (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1142/S0219649224501065

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